typo fixes and some logic update

detections/endpoint/linux_auditd_add_user_account.yml

@@ -9,7 +9,7 @@ description: The following analytic detects the creation of new user accounts on
 data_source:
 - Linux Auditd Proctitle
 search: '`linux_auditd` `linux_auditd_normalized_proctitle_process`| rename host as dest | where LIKE (process_exec, "%useradd%") OR LIKE (process_exec, "%adduser%") | stats count min(_time) as firstTime max(_time) as lastTime by process_exec proctitle dest  | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| `linux_auditd_add_user_account_filter`'
-how_to_implement: To implement this detection, the process begins by ingesting auditd data, that consist SYSCALL, TYPE, EXECVE and PROCTITLE events, which captures command-line executions and process details on Unix/Linux systems. These logs should be ingested and processed using Splunk Add-on for Unix and Linux (https://splunkbase.splunk.com/app/833), which is essential for correctly parsing and categorizing the data. The next step involves normalizing the field names  to match the field names set by the Splunk Common Information Model (CIM) to ensure consistency across different data sources and enhance the efficiency of data modeling. This approach enables effective monitoring and detection of linux endpoints where auditd is deployed
+how_to_implement: To implement this detection, the process begins by ingesting auditd data, that consists of SYSCALL, TYPE, EXECVE and PROCTITLE events, which captures command-line executions and process details on Unix/Linux systems. These logs should be ingested and processed using Splunk Add-on for Unix and Linux (https://splunkbase.splunk.com/app/833), which is essential for correctly parsing and categorizing the data. The next step involves normalizing the field names  to match the field names set by the Splunk Common Information Model (CIM) to ensure consistency across different data sources and enhance the efficiency of data modeling. This approach enables effective monitoring and detection of linux endpoints where auditd is deployed
 known_false_positives: Administrator or network operator can execute this command. Please update the filter macros to remove false positives.
 references:
 - https://linuxize.com/post/how-to-create-users-in-linux-using-the-useradd-command/

detections/endpoint/linux_auditd_add_user_account_type.yml

@@ -9,7 +9,7 @@ description: The following analytic detects the suspicious add user account type
 data_source:
 - Linux Auditd Add User
 search: '`linux_auditd` type=ADD_USER | rename hostname as dest| stats count min(_time) as firstTime max(_time) as lastTime by exe pid dest res UID type | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`| `linux_auditd_add_user_account_type_filter`'
-how_to_implement: To implement this detection, the process begins by ingesting auditd data, that consist SYSCALL, TYPE, EXECVE and PROCTITLE events, which captures command-line executions and process details on Unix/Linux systems. These logs should be ingested and processed using Splunk Add-on for Unix and Linux (https://splunkbase.splunk.com/app/833), which is essential for correctly parsing and categorizing the data. The next step involves normalizing the field names  to match the field names set by the Splunk Common Information Model (CIM) to ensure consistency across different data sources and enhance the efficiency of data modeling. This approach enables effective monitoring and detection of linux endpoints where auditd is deployed
+how_to_implement: To implement this detection, the process begins by ingesting auditd data, that consists of SYSCALL, TYPE, EXECVE and PROCTITLE events, which captures command-line executions and process details on Unix/Linux systems. These logs should be ingested and processed using Splunk Add-on for Unix and Linux (https://splunkbase.splunk.com/app/833), which is essential for correctly parsing and categorizing the data. The next step involves normalizing the field names  to match the field names set by the Splunk Common Information Model (CIM) to ensure consistency across different data sources and enhance the efficiency of data modeling. This approach enables effective monitoring and detection of linux endpoints where auditd is deployed
 known_false_positives: Administrator or network operator can use this application for automation purposes. Please update the filter macros to remove false positives.
 references:
 - https://www.splunk.com/en_us/blog/security/deep-dive-on-persistence-privilege-escalation-technique-and-detection-in-linux-platform.html

detections/endpoint/linux_auditd_at_application_execution.yml

@@ -9,7 +9,7 @@ description: The following analytic detects the execution of the "At" applicatio
 data_source:
 - Linux Auditd Syscall
 search: '`linux_auditd` type=SYSCALL comm IN ("at", "atd") OR exe IN ("/usr/bin/at","/usr/bin/atd") AND NOT (UID IN("daemon")) | rename host as dest | stats count min(_time) as firstTime max(_time) as lastTime by comm exe  SYSCALL UID ppid pid dest | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`| `linux_auditd_at_application_execution_filter`'
-how_to_implement: To implement this detection, the process begins by ingesting auditd data, that consist SYSCALL, TYPE, EXECVE and PROCTITLE events, which captures command-line executions and process details on Unix/Linux systems. These logs should be ingested and processed using Splunk Add-on for Unix and Linux (https://splunkbase.splunk.com/app/833), which is essential for correctly parsing and categorizing the data. The next step involves normalizing the field names  to match the field names set by the Splunk Common Information Model (CIM) to ensure consistency across different data sources and enhance the efficiency of data modeling. This approach enables effective monitoring and detection of linux endpoints where auditd is deployed
+how_to_implement: To implement this detection, the process begins by ingesting auditd data, that consists of SYSCALL, TYPE, EXECVE and PROCTITLE events, which captures command-line executions and process details on Unix/Linux systems. These logs should be ingested and processed using Splunk Add-on for Unix and Linux (https://splunkbase.splunk.com/app/833), which is essential for correctly parsing and categorizing the data. The next step involves normalizing the field names  to match the field names set by the Splunk Common Information Model (CIM) to ensure consistency across different data sources and enhance the efficiency of data modeling. This approach enables effective monitoring and detection of linux endpoints where auditd is deployed
 known_false_positives: Administrator or network operator can use this application for automation purposes. Please update the filter macros to remove false positives.
 references:
 - https://attack.mitre.org/techniques/T1053/001/

detections/endpoint/linux_auditd_auditd_service_stop.yml

@@ -9,7 +9,7 @@ description: The following analytic detects the suspicious auditd service stop.
 data_source:
 - Linux Auditd Service Stop
 search: '`linux_auditd` type=SERVICE_STOP unit IN ("auditd") | rename host as dest | stats count min(_time) as firstTime max(_time) as lastTime by type pid UID comm exe unit dest | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`| `linux_auditd_auditd_service_stop_filter`'
-how_to_implement: To implement this detection, the process begins by ingesting auditd data, that consist SYSCALL, TYPE, EXECVE and PROCTITLE events, which captures command-line executions and process details on Unix/Linux systems. These logs should be ingested and processed using Splunk Add-on for Unix and Linux (https://splunkbase.splunk.com/app/833), which is essential for correctly parsing and categorizing the data. The next step involves normalizing the field names  to match the field names set by the Splunk Common Information Model (CIM) to ensure consistency across different data sources and enhance the efficiency of data modeling. This approach enables effective monitoring and detection of linux endpoints where auditd is deployed
+how_to_implement: To implement this detection, the process begins by ingesting auditd data, that consists of SYSCALL, TYPE, EXECVE and PROCTITLE events, which captures command-line executions and process details on Unix/Linux systems. These logs should be ingested and processed using Splunk Add-on for Unix and Linux (https://splunkbase.splunk.com/app/833), which is essential for correctly parsing and categorizing the data. The next step involves normalizing the field names  to match the field names set by the Splunk Common Information Model (CIM) to ensure consistency across different data sources and enhance the efficiency of data modeling. This approach enables effective monitoring and detection of linux endpoints where auditd is deployed
 known_false_positives: Administrator or network operator can use this application for automation purposes. Please update the filter macros to remove false positives.
 references:
 - https://www.splunk.com/en_us/blog/security/deep-dive-on-persistence-privilege-escalation-technique-and-detection-in-linux-platform.html
@@ -31,7 +31,7 @@ tags:
   asset_type: Endpoint
   confidence: 50
   impact: 50
-  message: A service event - [$type$] event occured on host - [$dest$].
+  message: A service event - [$type$] event occurred on host - [$dest$].
   mitre_attack_id:
   - T1489
   observable:

detections/endpoint/linux_auditd_base64_decode_files.yml

@@ -9,7 +9,7 @@ description: The following analytic detects suspicious Base64 decode operations
 data_source:
 - Linux Auditd Execve
 search: '`linux_auditd` `linux_auditd_normalized_execve_process` | rename host as dest | where LIKE(process_exec, "%base64%") AND (LIKE(process_exec, "%-d %") OR LIKE(process_exec, "% --d%")) | stats count min(_time) as firstTime max(_time) as lastTime by argc process_exec dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| `linux_auditd_base64_decode_files_filter`'
-how_to_implement: To implement this detection, the process begins by ingesting auditd data, that consist SYSCALL, TYPE, EXECVE and PROCTITLE events, which captures command-line executions and process details on Unix/Linux systems. These logs should be ingested and processed using Splunk Add-on for Unix and Linux (https://splunkbase.splunk.com/app/833), which is essential for correctly parsing and categorizing the data. The next step involves normalizing the field names  to match the field names set by the Splunk Common Information Model (CIM) to ensure consistency across different data sources and enhance the efficiency of data modeling. This approach enables effective monitoring and detection of linux endpoints where auditd is deployed
+how_to_implement: To implement this detection, the process begins by ingesting auditd data, that consists of SYSCALL, TYPE, EXECVE and PROCTITLE events, which captures command-line executions and process details on Unix/Linux systems. These logs should be ingested and processed using Splunk Add-on for Unix and Linux (https://splunkbase.splunk.com/app/833), which is essential for correctly parsing and categorizing the data. The next step involves normalizing the field names  to match the field names set by the Splunk Common Information Model (CIM) to ensure consistency across different data sources and enhance the efficiency of data modeling. This approach enables effective monitoring and detection of linux endpoints where auditd is deployed
 known_false_positives: Administrator or network operator can use this application for automation purposes. Please update the filter macros to remove false positives.
 references:
 - https://www.splunk.com/en_us/blog/security/deep-dive-on-persistence-privilege-escalation-technique-and-detection-in-linux-platform.html

detections/endpoint/linux_auditd_change_file_owner_to_root.yml

@@ -9,7 +9,7 @@ description: The following analytic detects the use of the 'chown' command to ch
 data_source:
 - Linux Auditd Proctitle
 search: '`linux_auditd` `linux_auditd_normalized_proctitle_process`| rename host as dest | where LIKE (process_exec, "%chown %root%") | stats count min(_time) as firstTime max(_time) as lastTime by process_exec proctitle normalized_proctitle_delimiter dest | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`| `linux_auditd_change_file_owner_to_root_filter`'
-how_to_implement: To implement this detection, the process begins by ingesting auditd data, that consist SYSCALL, TYPE, EXECVE and PROCTITLE events, which captures command-line executions and process details on Unix/Linux systems. These logs should be ingested and processed using Splunk Add-on for Unix and Linux (https://splunkbase.splunk.com/app/833), which is essential for correctly parsing and categorizing the data. The next step involves normalizing the field names  to match the field names set by the Splunk Common Information Model (CIM) to ensure consistency across different data sources and enhance the efficiency of data modeling. This approach enables effective monitoring and detection of linux endpoints where auditd is deployed
+how_to_implement: To implement this detection, the process begins by ingesting auditd data, that consists of SYSCALL, TYPE, EXECVE and PROCTITLE events, which captures command-line executions and process details on Unix/Linux systems. These logs should be ingested and processed using Splunk Add-on for Unix and Linux (https://splunkbase.splunk.com/app/833), which is essential for correctly parsing and categorizing the data. The next step involves normalizing the field names  to match the field names set by the Splunk Common Information Model (CIM) to ensure consistency across different data sources and enhance the efficiency of data modeling. This approach enables effective monitoring and detection of linux endpoints where auditd is deployed
 known_false_positives: Administrator or network operator can execute this command. Please update the filter macros to remove false positives.
 references:
 - https://unix.stackexchange.com/questions/101073/how-to-change-permissions-from-root-user-to-all-users

detections/endpoint/linux_auditd_clipboard_data_copy.yml

@@ -9,7 +9,7 @@ description: The following analytic detects the use of the Linux 'xclip' command
 data_source:
 - Linux Auditd Execve
 search: '`linux_auditd` `linux_auditd_normalized_execve_process` | rename host as dest | where LIKE(process_exec, "%xclip%") AND (LIKE(process_exec, "%clipboard%") OR LIKE(process_exec, "%-o%") OR LIKE(process_exec, "%clip %") OR LIKE(process_exec, "%-selection %") OR LIKE(process_exec, "%sel %")) | stats count min(_time) as firstTime max(_time) as lastTime by argc process_exec dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| `linux_auditd_clipboard_data_copy_filter`'
-how_to_implement: To implement this detection, the process begins by ingesting auditd data, that consist SYSCALL, TYPE, EXECVE and PROCTITLE events, which captures command-line executions and process details on Unix/Linux systems. These logs should be ingested and processed using Splunk Add-on for Unix and Linux (https://splunkbase.splunk.com/app/833), which is essential for correctly parsing and categorizing the data. The next step involves normalizing the field names  to match the field names set by the Splunk Common Information Model (CIM) to ensure consistency across different data sources and enhance the efficiency of data modeling. This approach enables effective monitoring and detection of linux endpoints where auditd is deployed
+how_to_implement: To implement this detection, the process begins by ingesting auditd data, that consists of SYSCALL, TYPE, EXECVE and PROCTITLE events, which captures command-line executions and process details on Unix/Linux systems. These logs should be ingested and processed using Splunk Add-on for Unix and Linux (https://splunkbase.splunk.com/app/833), which is essential for correctly parsing and categorizing the data. The next step involves normalizing the field names  to match the field names set by the Splunk Common Information Model (CIM) to ensure consistency across different data sources and enhance the efficiency of data modeling. This approach enables effective monitoring and detection of linux endpoints where auditd is deployed
 known_false_positives: False positives may be present on Linux desktop as it may commonly be used by administrators or end users. Filter as needed.
 references:
 - https://attack.mitre.org/techniques/T1115/

detections/endpoint/linux_auditd_data_destruction_command.yml

@@ -9,7 +9,7 @@ description: The following analytic detects the execution of a Unix shell comman
 data_source:
 - Linux Auditd Execve
 search: '`linux_auditd` `linux_auditd_normalized_execve_process` | rename host as dest | where LIKE (process_exec, "%rm %") AND LIKE (process_exec, "% -rf %") AND LIKE (process_exec, "%--no-preserve-root%") | stats count min(_time) as firstTime max(_time) as lastTime by argc process_exec dest | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`| `linux_auditd_data_destruction_command_filter`'
-how_to_implement: To implement this detection, the process begins by ingesting auditd data, that consist SYSCALL, TYPE, EXECVE and PROCTITLE events, which captures command-line executions and process details on Unix/Linux systems. These logs should be ingested and processed using Splunk Add-on for Unix and Linux (https://splunkbase.splunk.com/app/833), which is essential for correctly parsing and categorizing the data. The next step involves normalizing the field names  to match the field names set by the Splunk Common Information Model (CIM) to ensure consistency across different data sources and enhance the efficiency of data modeling. This approach enables effective monitoring and detection of linux endpoints where auditd is deployed
+how_to_implement: To implement this detection, the process begins by ingesting auditd data, that consists of SYSCALL, TYPE, EXECVE and PROCTITLE events, which captures command-line executions and process details on Unix/Linux systems. These logs should be ingested and processed using Splunk Add-on for Unix and Linux (https://splunkbase.splunk.com/app/833), which is essential for correctly parsing and categorizing the data. The next step involves normalizing the field names  to match the field names set by the Splunk Common Information Model (CIM) to ensure consistency across different data sources and enhance the efficiency of data modeling. This approach enables effective monitoring and detection of linux endpoints where auditd is deployed
 known_false_positives: unknown
 references:
 - https://cert.gov.ua/article/3718487